Accurately georeferenced mosaics of orthophotos, referred to as orthomosaics, are becoming popular alternatives to traditional pictorial maps because they can be created automatically from aerial photos, and because they show actual useful detail on the ground.
The creation of accurate orthomosaics from aerial photos is well described in the literature. See, for example, Elements of Photogrammetry with Application in GIS, Fourth Edition (Wolf et al.) (McGraw-Hill 2014), and the Manual of Photogrammetry, Sixth Edition (American Society for Photogrammetry and Remote Sensing (ASPRS) 2013).
The creation of an orthomosaic requires the systematic capture of overlapping aerial photos of the area of interest, both to ensure complete coverage of the area of interest, and to ensure that there is sufficient redundancy in the imagery to allow accurate bundle adjustment, orthorectification and alignment of the photos.
Bundle adjustment is the process by which redundant estimates of ground points and camera poses are refined. Modern bundle adjustment is described in detail in “Bundle Adjustment—A Modern Synthesis” (Triggs et al.) in Vision Algorithms: Theory and Practice (Lecture Notes in Computer Science, Volume 1883, Springer 2000).
Bundle adjustment may operate on the positions of manually-identified ground points, or, increasingly, on the positions of automatically-identified ground features which are automatically matched between overlapping photos.
Overlapping aerial photos are typically captured by navigating a survey aircraft in a serpentine pattern over the area of interest. The survey aircraft carries an aerial camera system, and the serpentine flight pattern ensures that the photos captured by the camera system overlap both along flight lines within the flight pattern and between adjacent flight lines.
The aerial camera system carried by a survey aircraft sees a larger view of the ground when the aircraft is operated at a higher altitude. This allows the spacing of flight lines to be increased and hence survey efficiency to be improved. However, to maintain a particular ground sampling distance, i.e. the spacing of camera pixels on the ground, larger camera image sensors or more cameras may need to used.